Image-to-Image
Diffusers
Safetensors
image-decomposition
layered-image-editing
diffusion
flux
lora
transparent-rgba
Instructions to use SynLayers/synlayers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SynLayers/synlayers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SynLayers/synlayers") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things

- Xet hash:
- 13811174f56549e0628e3758e7761da624becd34209b9cacc45619dc0e0c8809
- Size of remote file:
- 593 kB
- SHA256:
- 1b179166760487e9b2df3cc1f9f3311ea0fc1c5b0f09827ad47a21e60cb0218e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.